Category Archives: Artificial Intelligence

This post follows the Bearish Case of Digital Transformation. The bullish case of Digital Transformation is a scenario where productivity growth in many industries approaches 3% or higher for a sustained period (2020+) and the product/service quality is continuously improving.

There is a good chance that the bullish case comes true, especially if advances in foundational components of Digital Transformation feed each other and geo-political conditions return to a tranquil state.

In the benign scenario, Moore’s law continues to hold true for computing, ubiquitous communications (mobile and fixed broadband) become dirt cheap, mobile phones are miniature super computers with unlimited intelligence and computing power aided by Cloud Computing, Artificial Intelligence endows robots to become reasonably autonomous and intelligent to eliminate human drudgery, clean energy is ubiquitous and cheaper than the cheapest fossil fuel and genomics/synthetic biology eliminate disease and ensure sustainable and plentiful food supply. Sounds like Utopia? This is the type of future many techno-utopians imagine to be coming.

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We can see that a broad discussion on boom or gloom scenarios for the world economy is taking place across the political and economic spectrum based on this New York Times article. How technological innovation increases productivity is at the center of this debate. It aligns nicely with the raging debate and marketing hype around digital transformation.

The marketing hype unleashed by the technology-consulting-analyst industrial complex would lead us to believe that we are at the onset of unprecedented age of growth based on intelligent machines, robotics, cloud computing, big data, new materials, 3D printing, synthetic biology, hyper connectivity, etc. A timely illumination on this topic comes from Dr. Robert J. Gordon in the form of very impressive, “The Rise and Fall of American Growth.” Dr. Gordon’s contention is that advances in technology of the last 3 decades have not been as transformational to the human kind as the ones that happened between 1870 and 1970. He argues the following (from the book)

Economic growth since 1970 has been simultaneously dazzling and disappointing. This paradox is resolved when we recognize that advances since 1970 have tended to be channeled into a narrow sphere of human activity having to do with entertainment, communications, and the collection and processing of information. For the rest of what humans care about—food, clothing, shelter, transportation, health, and working conditions both inside and outside the home—progress slowed down after 1970, both qualitatively and quantitatively.

One way to forecast (bullish or bearish) impact of Digital Transformation over the next few decades (20-30 years) is to see how various elements of Digital Transformation influence different industries.

We can arrive at a bullish case for Digital Transformation if the element(s) of Digital Transformation have a beneficial impact on the productivity and product/service quality in different industries. The bears will triumph if the impact is minimal and/or major headwinds persist for broad adoption of elements of Digital Transformation.

The following elements are generally seen as the foundation for Digital Transformation.

Mobile and Cloud Computing

Internet of Things (Sensors, Intelligent Machines, etc.)

Robotics

Artificial Intelligence

Genomics and Synthetic Biology

New Energy Sources

We will first test the (bullish and bearish) thesis by creating a prognosis of the beneficial impact of the above on various industries from the NAICS industry classification in the table below.

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INDUSTRY

MOBILE AND CLOUD COMPUTING

INTERNET OF THINGS

ARTIFICIAL INTELLIGENCE

ROBOTICS

GENOMICS AND SYNTHETIC BIOLOGY

NEW ENERGY SOURCES

Accommodation and Food Services

Very High

High

Low

Low

Low

Low

Administrative and Support

High

High

Very High

Moderate

Low

Low

Agriculture, Forestry, Fishing and Hunting

Moderate

High

Moderate

High

Very High

Low Impact

Arts, Entertainment, and Recreation

Very High

High

High

High

Low

Low

Construction

Moderate

High

Moderate

High

Low

Low

Educational Services

Very High

Low

Very High

Low

Low

Low

Finance and Insurance

High

High

Very High

Low

Low

Low

Government

Very High

High

Moderate

Moderate

Low

Moderate

Health Care

High

Very High

Very High

Very High

Very High

Low

Information

Very High

Very High

Very High

Moderate

High

None

Manufacturing

Moderate

High

High

Very High

Low

Moderate

Mining, Quarrying, and Oil and Gas Extraction

Low

High

Moderate

High

Low

Very High

Professional, Scientific, and Technical Services

High

High

Very High

Very High

Low

Low

Real Estate and Rental and Leasing

Moderate

High

Low

Low

No

Moderate

Retail Trade

High

High

Moderate

Moderate

None

Low

Transportation and Warehousing

Moderate

High

Very High

High

None

High

Utilities

Moderate

Very High

Moderate

High

Low

Very High

Wholesale Trade

Moderate

High

Moderate

Low

None

Low

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As we can see from the table above digital transformation has a beneficial impact mostly on information rich industries. Large parts of the real economy, like construction, agriculture, retail, trade and government may not see much in terms of positive impact on productivity and product/service quality. In addition, major headwinds listed below can act as obstacles to widespread adoption of elements of digital transformation or lead to failure in realization of significant productivity gains, positive outcomes and/or improvement in product/service quality.

Adoption of mobile computing is closing on saturation levels globally and no more productivity gains are to be realized due to lack of original iPhone (in 2007) level innovation

Adoption of Internet of Things in various industries does not take off due to lack of interoperability, limited user adoption, regulatory hurdles, security issues and limited marginal utility for end customers

Artificial Intelligence hits major roadblocks again due to low trust and reliability

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In the age of social media it’s hard to pay attention to more than 2 paragraphs of text at a time. It’s highly unlikely that you will find the time, interest and initiative to read 167 pages of the ominous sounding “Future of Jobs” report from World Economic Forum (WEF). So we did for you, subtracted all the fluff and abridged the report into this lucid post. First a few bullet points.

Advances in genetics, artificial intelligence, robotics, nanotechnology, 3D printing and biotechnology are laying a foundation for a revolution.

Most occupations are undergoing fundamental transformation. Some jobs are threatened by redundancy, other growing rapidly and existing jobs require change in skill sets.

The worst case scenario could be talent shortages coupled with mass unemployment and growing inequality,

65% of children entering primary school today will end up doing job types that do not exist today

The top 5 drivers of change are

Changing nature of work and flexible work

Mobile, Internet and Cloud technologies

Increasing processing power and big data

Middle class in emerging markets

Climate change

Most of the drivers support job growth. A few, including geopolitical volatility, artificial intelligence, could lead to job losses.

Computing, mathematical and engineering job types will see the highest growth prospects, while office/administrative and manufacturing/production job types will see contraction.

The authors of the report themselves admit that the report does not offer any prognosis for the largest segment of job type in the world, especially in developing economies; Farming, Fishing and Forestry.

Two new job types that were most frequently mentioned are data analysts and specialized sales representatives.

The report highlights core work-related skills (Figure 9 – Page 21) that seemed to have come out of a Common Core evaluation form.

It was surprising to see that women make between 30-40% less than men in many industries. The top 3 barriers to gender parity are

Unconscious bias among managers

Lack of work-life balance

Lack of role models

The report has a lot more information on above topics, different regions of the world and industries. It is a worthy effort to understand how HR departments in large companies perceive the jobs conundrum. The report would be lot more comprehensive if it had covered the crystal ball for the vast majority of people that work in the informal sector in the developing world and emerging economies.